Difference between revisions of "Lab: Semantic Lifting - CSV"
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Revision as of 20:15, 12 March 2020
Lab 9: Semantic Lifting - CSV
- Group Presentations.
- SPARQL programming in python with SPARQLWrapper and Blazegraph, or alternatively RDFlib.
Today you will be presenting your ideas for the group project in the lab. Andreas Opdahl will be present to give you further feedback and ideas.
Tasks (if we have additional time)
After the presentations you can start on the tasks for next week. These tasks are about programming SPARQL queries and inserts in a python program. Last week we added triples manually from the web interface.
However, sometimes we would rather want to program the insertion or updates of triples for our graphs/databases.
- Redo all the SPARQL queries and updates from Lab 4, this time writing a Python program.
The most important part is that we need to import a SPARQLWrapper in order to connect to the SPARQL endpoint of Blazegraph. When it comes to how to do some queries I recommend scrolling down on this page for help: https://github.com/RDFLib/sparqlwrapper
Remember, before you can program with Blazegraph you have to make sure its running like we did in Lab 4. Now you will be able to program queries and updates.
# How to establish connection to Blazegraph endpoint. from SPARQLWrapper import SPARQLWrapper, JSON sparql = SPARQLWrapper("("http://localhost:9999/bigdata/sparql")")
If you have not been able to run Blazegraph yet, you can instead program SPARQL queries directly with RDFlib.
For help, look at the link below: